{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analyze Order Book Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imports & Settings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:52.402508Z",
     "start_time": "2020-06-13T21:17:51.801463Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from pathlib import Path\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import FuncFormatter\n",
    "from math import pi\n",
    "from bokeh.plotting import figure, show\n",
    "from scipy.stats import normaltest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:52.407149Z",
     "start_time": "2020-06-13T21:17:52.403849Z"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "pd.set_option('display.float_format', lambda x: '%.2f' % x)\n",
    "sns.set_style('whitegrid')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:52.418012Z",
     "start_time": "2020-06-13T21:17:52.408308Z"
    }
   },
   "outputs": [],
   "source": [
    "data_path = Path('data')\n",
    "itch_store = str(data_path / 'itch.h5')\n",
    "order_book_store = str(data_path / 'order_book.h5')\n",
    "stock = 'AAPL'\n",
    "date = '20191030'\n",
    "title = '{} | {}'.format(stock, pd.to_datetime(date).date())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load system event data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:52.461029Z",
     "start_time": "2020-06-13T21:17:52.418915Z"
    }
   },
   "outputs": [],
   "source": [
    "with pd.HDFStore(itch_store) as store:\n",
    "    sys_events = store['S'].set_index('event_code').drop_duplicates()\n",
    "    sys_events.timestamp = sys_events.timestamp.add(pd.to_datetime(date)).dt.time\n",
    "    market_open = sys_events.loc['Q', 'timestamp']\n",
    "    market_close = sys_events.loc['M', 'timestamp']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Trade Summary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will combine the messages that refer to actual trades to learn about the volumes for each asset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:52.570879Z",
     "start_time": "2020-06-13T21:17:52.461891Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 8887 entries, 0 to 8886\n",
      "Data columns (total 17 columns):\n",
      " #   Column                          Non-Null Count  Dtype          \n",
      "---  ------                          --------------  -----          \n",
      " 0   stock_locate                    8887 non-null   int64          \n",
      " 1   tracking_number                 8887 non-null   int64          \n",
      " 2   timestamp                       8887 non-null   timedelta64[ns]\n",
      " 3   stock                           8887 non-null   object         \n",
      " 4   market_category                 8887 non-null   object         \n",
      " 5   financial_status_indicator      8887 non-null   object         \n",
      " 6   round_lot_size                  8887 non-null   int64          \n",
      " 7   round_lots_only                 8887 non-null   object         \n",
      " 8   issue_classification            8887 non-null   object         \n",
      " 9   issue_sub_type                  8887 non-null   object         \n",
      " 10  authenticity                    8887 non-null   object         \n",
      " 11  short_sale_threshold_indicator  8887 non-null   object         \n",
      " 12  ipo_flag                        8887 non-null   object         \n",
      " 13  luld_reference_price_tier       8887 non-null   object         \n",
      " 14  etp_flag                        8887 non-null   object         \n",
      " 15  etp_leverage_factor             8887 non-null   int64          \n",
      " 16  inverse_indicator               8887 non-null   object         \n",
      "dtypes: int64(4), object(12), timedelta64[ns](1)\n",
      "memory usage: 1.2+ MB\n"
     ]
    }
   ],
   "source": [
    "with pd.HDFStore(itch_store) as store:\n",
    "    stocks = store['R']\n",
    "stocks.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As expected, a small number of the over 8,500 equity securities traded on this day account for most trades"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:53.692332Z",
     "start_time": "2020-06-13T21:17:52.571887Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "with pd.HDFStore(itch_store) as store:\n",
    "    stocks = store['R'].loc[:, ['stock_locate', 'stock']]\n",
    "    trades = store['P'].append(store['Q'].rename(columns={'cross_price': 'price'}), sort=False).merge(stocks)\n",
    "\n",
    "trades['value'] = trades.shares.mul(trades.price)    \n",
    "trades['value_share'] = trades.value.div(trades.value.sum())\n",
    "trade_summary = trades.groupby('stock').value_share.sum().sort_values(ascending=False)\n",
    "trade_summary.iloc[:50].plot.bar(figsize=(14, 6), color='darkblue', title='% of Traded Value')\n",
    "plt.gca().yaxis.set_major_formatter(FuncFormatter(lambda y, _: '{:.0%}'.format(y)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## AAPL Trade Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:53.708315Z",
     "start_time": "2020-06-13T21:17:53.693645Z"
    }
   },
   "outputs": [],
   "source": [
    "with pd.HDFStore(order_book_store) as store:\n",
    "    trades = store['{}/trades'.format(stock)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:53.724127Z",
     "start_time": "2020-06-13T21:17:53.710711Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 58713 entries, 2019-10-30 09:30:00.010384780 to 2019-10-30 15:59:59.979015439\n",
      "Data columns (total 2 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   shares  58713 non-null  int64  \n",
      " 1   price   58713 non-null  float64\n",
      "dtypes: float64(1), int64(1)\n",
      "memory usage: 1.3 MB\n"
     ]
    }
   ],
   "source": [
    "trades.price = trades.price.mul(1e-4) # format price\n",
    "trades = trades[trades.cross == 0]\n",
    "trades = trades.between_time(market_open, market_close).drop('cross', axis=1)\n",
    "trades.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tick Bars"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The trade data is indexed by nanoseconds and is very noisy. The bid-ask bounce, for instance, causes the price to oscillate between the bid and ask prices when trade initiation alternates between buy and sell market orders. To improve the noise-signal ratio and improve the statistical properties, we need to resample and regularize the tick data by aggregating the trading activity."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We typically collect the open (first), low, high, and closing (last) price for the aggregated period, alongside the volume-weighted average price (VWAP), the number of shares traded, and the timestamp associated with the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:54.286172Z",
     "start_time": "2020-06-13T21:17:53.725223Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tick_bars = trades.copy()\n",
    "tick_bars.index = tick_bars.index.time\n",
    "tick_bars.price.plot(figsize=(10, 5), \n",
    "                     title='Tick Bars | {} | {}'.format(stock, pd.to_datetime(date).date()), lw=1)\n",
    "plt.xlabel('')\n",
    "plt.tight_layout();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Test for Normality of tick returns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:54.293686Z",
     "start_time": "2020-06-13T21:17:54.287095Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NormaltestResult(statistic=20684.40456159484, pvalue=0.0)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "normaltest(tick_bars.price.pct_change().dropna())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Regularizing Tick Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Price-Volume Chart"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will use the `price_volume` function to compare the price-volume relation for various regularization methods."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:54.304784Z",
     "start_time": "2020-06-13T21:17:54.294973Z"
    }
   },
   "outputs": [],
   "source": [
    "def price_volume(df, price='vwap', vol='vol', suptitle=title, fname=None):\n",
    "    \n",
    "    fig, axes = plt.subplots(nrows=2, sharex=True, figsize=(15,8))\n",
    "    axes[0].plot(df.index, df[price])\n",
    "    axes[1].bar(df.index, df[vol], width=1/(5*len(df.index)), color='r')\n",
    "    \n",
    "    # formatting\n",
    "    xfmt = mpl.dates.DateFormatter('%H:%M')\n",
    "    axes[1].xaxis.set_major_locator(mpl.dates.HourLocator(interval=3))\n",
    "    axes[1].xaxis.set_major_formatter(xfmt)\n",
    "    axes[1].get_xaxis().set_tick_params(which='major', pad=25)\n",
    "    axes[0].set_title('Price', fontsize=14)\n",
    "    axes[1].set_title('Volume', fontsize=14)\n",
    "    fig.autofmt_xdate()\n",
    "    fig.suptitle(suptitle)\n",
    "    fig.tight_layout()\n",
    "    plt.subplots_adjust(top=0.9);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Time Bars"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Time bars involve trade aggregation by period."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:54.313753Z",
     "start_time": "2020-06-13T21:17:54.305774Z"
    }
   },
   "outputs": [],
   "source": [
    "def get_bar_stats(agg_trades):\n",
    "    vwap = agg_trades.apply(lambda x: np.average(x.price, weights=x.shares)).to_frame('vwap')\n",
    "    ohlc = agg_trades.price.ohlc()\n",
    "    vol = agg_trades.shares.sum().to_frame('vol')\n",
    "    txn = agg_trades.shares.size().to_frame('txn')\n",
    "    return pd.concat([ohlc, vwap, vol, txn], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We create time bars using the `.resample()` method with the desired period."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:54.388607Z",
     "start_time": "2020-06-13T21:17:54.314956Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NormaltestResult(statistic=65.70387182967823, pvalue=5.402384769537968e-15)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "resampled = trades.groupby(pd.Grouper(freq='1Min'))\n",
    "time_bars = get_bar_stats(resampled)\n",
    "normaltest(time_bars.vwap.pct_change().dropna())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:55.590306Z",
     "start_time": "2020-06-13T21:17:54.389511Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1080x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "price_volume(time_bars, \n",
    "             suptitle=f'Time Bars | {stock} | {pd.to_datetime(date).date()}', \n",
    "             fname='time_bars')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bokeh Candlestick Chart"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alternative visualization using the the [bokeh](https://bokeh.pydata.org/en/latest/) library:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:56.003654Z",
     "start_time": "2020-06-13T21:17:55.591334Z"
    },
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "resampled = trades.groupby(pd.Grouper(freq='5Min')) # 5 Min bars for better print\n",
    "df = get_bar_stats(resampled)\n",
    "\n",
    "increase = df.close > df.open\n",
    "decrease = df.open > df.close\n",
    "w = 2.5 * 60 * 1000 # 2.5 min in ms\n",
    "\n",
    "WIDGETS = \"pan, wheel_zoom, box_zoom, reset, save\"\n",
    "\n",
    "p = figure(x_axis_type='datetime', tools=WIDGETS, plot_width=1500, title = \"AAPL Candlestick\")\n",
    "p.xaxis.major_label_orientation = pi/4\n",
    "p.grid.grid_line_alpha=0.4\n",
    "\n",
    "p.segment(df.index, df.high, df.index, df.low, color=\"black\")\n",
    "p.vbar(df.index[increase], w, df.open[increase], df.close[increase], fill_color=\"#D5E1DD\", line_color=\"black\")\n",
    "p.vbar(df.index[decrease], w, df.open[decrease], df.close[decrease], fill_color=\"#F2583E\", line_color=\"black\")\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Volume Bars"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Time bars smooth some of the noise contained in the raw tick data but may fail to account for the fragmentation of orders. Execution-focused algorithmic trading may aim to match the volume weighted average price (VWAP) over a given period, and will divide a single order into multiple trades and place orders according to historical patterns. Time bars would treat the same order differently, even though no new information has arrived in the market.\n",
    "\n",
    "Volume bars offer an alternative by aggregating trade data according to volume. We can accomplish this as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:56.025027Z",
     "start_time": "2020-06-13T21:17:56.004913Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 58713 entries, 2019-10-30 09:30:00.010384780 to 2019-10-30 15:59:59.979015439\n",
      "Data columns (total 2 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   shares  58713 non-null  int64  \n",
      " 1   price   58713 non-null  float64\n",
      "dtypes: float64(1), int64(1)\n",
      "memory usage: 1.3 MB\n"
     ]
    }
   ],
   "source": [
    "with pd.HDFStore(order_book_store) as store:\n",
    "    trades = store['{}/trades'.format(stock)]\n",
    "\n",
    "trades.price = trades.price.mul(1e-4)\n",
    "trades = trades[trades.cross == 0]\n",
    "trades = trades.between_time(market_open, market_close).drop('cross', axis=1)\n",
    "trades.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:56.031364Z",
     "start_time": "2020-06-13T21:17:56.026266Z"
    }
   },
   "outputs": [],
   "source": [
    "trades_per_min = trades.shares.sum()/(60*7.5) # min per trading day\n",
    "trades['cumul_vol'] = trades.shares.cumsum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:56.099714Z",
     "start_time": "2020-06-13T21:17:56.032671Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>timestamp</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>vwap</th>\n",
       "      <th>vol</th>\n",
       "      <th>txn</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cumul_vol</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-10-30 09:30:01.658183871</td>\n",
       "      <td>244.83</td>\n",
       "      <td>244.94</td>\n",
       "      <td>244.72</td>\n",
       "      <td>244.82</td>\n",
       "      <td>244.77</td>\n",
       "      <td>5317</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-10-30 09:30:02.124784227</td>\n",
       "      <td>244.82</td>\n",
       "      <td>244.85</td>\n",
       "      <td>244.76</td>\n",
       "      <td>244.77</td>\n",
       "      <td>244.79</td>\n",
       "      <td>9127</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-10-30 09:30:04.690393971</td>\n",
       "      <td>244.77</td>\n",
       "      <td>244.97</td>\n",
       "      <td>244.66</td>\n",
       "      <td>244.97</td>\n",
       "      <td>244.80</td>\n",
       "      <td>12257</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-10-30 09:30:13.816494419</td>\n",
       "      <td>244.98</td>\n",
       "      <td>245.00</td>\n",
       "      <td>244.88</td>\n",
       "      <td>245.00</td>\n",
       "      <td>244.98</td>\n",
       "      <td>10675</td>\n",
       "      <td>124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-10-30 09:30:17.522394656</td>\n",
       "      <td>245.00</td>\n",
       "      <td>245.25</td>\n",
       "      <td>245.00</td>\n",
       "      <td>245.10</td>\n",
       "      <td>245.10</td>\n",
       "      <td>10679</td>\n",
       "      <td>118</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              timestamp   open   high    low  close   vwap  \\\n",
       "cumul_vol                                                                    \n",
       "0         2019-10-30 09:30:01.658183871 244.83 244.94 244.72 244.82 244.77   \n",
       "1         2019-10-30 09:30:02.124784227 244.82 244.85 244.76 244.77 244.79   \n",
       "2         2019-10-30 09:30:04.690393971 244.77 244.97 244.66 244.97 244.80   \n",
       "3         2019-10-30 09:30:13.816494419 244.98 245.00 244.88 245.00 244.98   \n",
       "4         2019-10-30 09:30:17.522394656 245.00 245.25 245.00 245.10 245.10   \n",
       "\n",
       "             vol  txn  \n",
       "cumul_vol              \n",
       "0           5317   57  \n",
       "1           9127   44  \n",
       "2          12257   76  \n",
       "3          10675  124  \n",
       "4          10679  118  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = trades.reset_index()\n",
    "by_vol = df.groupby(df.cumul_vol.div(trades_per_min).round().astype(int))\n",
    "vol_bars = pd.concat([by_vol.timestamp.last().to_frame('timestamp'), get_bar_stats(by_vol)], axis=1)\n",
    "vol_bars.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:57.374645Z",
     "start_time": "2020-06-13T21:17:56.101240Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1080x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "price_volume(vol_bars.set_index('timestamp'), \n",
    "             suptitle=f'Volume Bars | {stock} | {pd.to_datetime(date).date()}', \n",
    "             fname='volume_bars')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:57.381916Z",
     "start_time": "2020-06-13T21:17:57.375444Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NormaltestResult(statistic=26.54669921949387, pvalue=1.7197190736584466e-06)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "normaltest(vol_bars.vwap.dropna())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dollar Bars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:57.408845Z",
     "start_time": "2020-06-13T21:17:57.383356Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 58713 entries, 2019-10-30 09:30:00.010384780 to 2019-10-30 15:59:59.979015439\n",
      "Data columns (total 2 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   shares  58713 non-null  int64  \n",
      " 1   price   58713 non-null  float64\n",
      "dtypes: float64(1), int64(1)\n",
      "memory usage: 1.3 MB\n"
     ]
    }
   ],
   "source": [
    "with pd.HDFStore(order_book_store) as store:\n",
    "    trades = store['{}/trades'.format(stock)]\n",
    "\n",
    "trades.price = trades.price.mul(1e-4)\n",
    "trades = trades[trades.cross == 0]\n",
    "trades = trades.between_time(market_open, market_close).drop('cross', axis=1)\n",
    "trades.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:57.416371Z",
     "start_time": "2020-06-13T21:17:57.410839Z"
    }
   },
   "outputs": [],
   "source": [
    "value_per_min = trades.shares.mul(trades.price).sum()/(60*7.5) # min per trading day\n",
    "trades['cumul_val'] = trades.shares.mul(trades.price).cumsum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:57.478518Z",
     "start_time": "2020-06-13T21:17:57.417460Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>timestamp</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>vwap</th>\n",
       "      <th>vol</th>\n",
       "      <th>txn</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cumul_val</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-10-30 09:30:01.658171058</td>\n",
       "      <td>244.83</td>\n",
       "      <td>244.94</td>\n",
       "      <td>244.72</td>\n",
       "      <td>244.82</td>\n",
       "      <td>244.77</td>\n",
       "      <td>5287</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-10-30 09:30:02.124784227</td>\n",
       "      <td>244.82</td>\n",
       "      <td>244.85</td>\n",
       "      <td>244.76</td>\n",
       "      <td>244.77</td>\n",
       "      <td>244.79</td>\n",
       "      <td>9157</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-10-30 09:30:04.095544194</td>\n",
       "      <td>244.77</td>\n",
       "      <td>244.96</td>\n",
       "      <td>244.66</td>\n",
       "      <td>244.87</td>\n",
       "      <td>244.80</td>\n",
       "      <td>12047</td>\n",
       "      <td>71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-10-30 09:30:13.816494419</td>\n",
       "      <td>244.87</td>\n",
       "      <td>245.00</td>\n",
       "      <td>244.87</td>\n",
       "      <td>245.00</td>\n",
       "      <td>244.98</td>\n",
       "      <td>10474</td>\n",
       "      <td>127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-10-30 09:30:17.522098123</td>\n",
       "      <td>245.00</td>\n",
       "      <td>245.25</td>\n",
       "      <td>245.00</td>\n",
       "      <td>245.13</td>\n",
       "      <td>245.09</td>\n",
       "      <td>10690</td>\n",
       "      <td>116</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              timestamp   open   high    low  close   vwap  \\\n",
       "cumul_val                                                                    \n",
       "0         2019-10-30 09:30:01.658171058 244.83 244.94 244.72 244.82 244.77   \n",
       "1         2019-10-30 09:30:02.124784227 244.82 244.85 244.76 244.77 244.79   \n",
       "2         2019-10-30 09:30:04.095544194 244.77 244.96 244.66 244.87 244.80   \n",
       "3         2019-10-30 09:30:13.816494419 244.87 245.00 244.87 245.00 244.98   \n",
       "4         2019-10-30 09:30:17.522098123 245.00 245.25 245.00 245.13 245.09   \n",
       "\n",
       "             vol  txn  \n",
       "cumul_val              \n",
       "0           5287   56  \n",
       "1           9157   45  \n",
       "2          12047   71  \n",
       "3          10474  127  \n",
       "4          10690  116  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = trades.reset_index()\n",
    "by_value = df.groupby(df.cumul_val.div(value_per_min).round().astype(int))\n",
    "dollar_bars = pd.concat([by_value.timestamp.last().to_frame('timestamp'), get_bar_stats(by_value)], axis=1)\n",
    "dollar_bars.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-13T21:17:58.797887Z",
     "start_time": "2020-06-13T21:17:57.479575Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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uXKgtW7bI6/VKkpYuXaqcnBzNmTNHBw4ckNfr1aJFi1RUVKStW7fq0UcfVVZWlsrKynTvvfcmtZAAAAAAAKBrM7wD49lnn9W8efMUDAYlSY8++qgefvhh1dXV6eqrr9azzz4rSdqxY4eWL1+uuro61dXVqbCwUCtXrlRJSYlefPFF3XTTTVq6dKkkaf78+aqtrdXKlSu1bds27dixI4lFTCMtLSf+AQAAAACQYQwTGMXFxVqyZEn768WLF2vgwIGSpLa2NuXl5en48ePau3evHnnkEU2aNElr1qyRJNXX12vkyJGSpFGjRsnn8ykQCKi1tVXFxcXyeDwqKyuTz+dLRtnST37+iX8AAAAAAGQYw0dIRo8erc8//7z9da9evSRJW7Zs0QsvvKAVK1bom2++0e23364pU6aora1NkydP1uDBgxUIBFRYWChJ8nq9ampqUiAQUEFBQfv2vF6vPvvsM8NAg8Gg/H6/5QJ2ReEEkaSTyhyeHu04xJsHpKuWlhZLdT6V7SRd2qgbyhGrjwSQPLS7xFkdsxLhhr4aMIv+BVaY+g6MSK+99pqefvppPfPMMyoqKmpPWnTv3l2SNHz4cDU2NqqgoEDNzc2SpObmZvXo0eOkaR2nG8nLyzupcmeKaGWOdxwy8Rghc/n9flt1PpXtJF3aqFvK4ZY4gExCu7PH7piVCM4Vupq0rbMtLSfupA//D0OxklmWf4XklVde0QsvvKC6ujr17dtXkrRnzx5VVFSora1NR48e1ZYtWzRo0CBdcskl2rhxoyRp06ZNuvTSS1VQUKCcnBx9+umnCoVC2rx5s4YNG5ZA0QAAAAAAcKn8fMnjIXnhAEt3YLS1tenRRx/VWWedpaqqKknSZZddph//+McaO3asbrnlFuXk5GjcuHE6//zz1adPH82dO1fl5eXKyclRbW2tJGnBggWaPXu22traVFZWpiFDhjhfMgAAAAAAkDY8oVAolOogzEjFbXcp5fFIXePUACmTcf0CvkUfCXQ+2l1CGLOAODKhf8mEMjooVp9p+RES2MDPnwIAAAAAOkuavge19SWesCiTn3UKN5pMPgYAAAAA0JnS9P0XCQwkV5o2HAAAAABpjA9iXYlHSAAAiBS+aEnDWy8BAIAJ+fkkL1yIOzAAAIgU/rkzvmwLAADANbgDAwAAAAAAt+GO0FOQwAAAfIuBEmak6TebuwbtEAAgfXtHKI+ytOMRErhbS8uJBhv+H0By8egEzKA/Ti7aIQAAUXEHRleQrp90mfmEKXwRF7kO0NUl2q75hBYAAAAZhjswuoJ0/aTLyidMfBqFdJNou6ZNAOmFn+sDAMAQd2AAQDqLvNODOzcAd+Ln+gCkK649Ok8GHGsSGDBmtiFkQIMBupzIN0V8GVR6oL8F4LR0fWQZqZdp1x4tLdKRI9/+3Zky4FiTwOhsTg0OsS5enRx8wtsy2xAyoMFkDN4cwWlcGDuL/hZwXqaPfV3xLqBMP2eRGGvdIT9f6t6dcTpJSGB0NqcGh8gvt7SyfbOdm1OxMrh0PWbfHJk5twymkLrmhXEs1GlkgmTVczdfEyQzMdjSooEDB7qz3F0ZydyTmR1r3dwOYU4GX4uQwHCbeBXxyJFT50dLZBh1SpGdW7IbQKYOLk7ebePWDsrMuY01mLpl8Iz2HRGpjsltOp6r8C2R4f4o0V9SSdaxjrftRPfrdDImFW0h2ftM5NFDt/QNmS5ZSUer1wRG7TVVj7l23J6VX1ULl9uJeDqjHScriWV1u+Hlo10Lx1veqXEg0WPttn7NyQ+qnFjHSWbOfbz5btYx9nh99O7dXbN8JpHA6AxWHvcIV8Tdu0/tpLt3j33nRcftd+yUOr7ZCP8dXjb8OtwAosUTeVFpZuCwO2gYrbd797dlifWGM5EBy+lOumPHksib5MjtRL6BjBaTmX05fWFidXvRBk8zF6odjvn5ffsmHle074iI1R6M9iNZe+YxvI9YF8KRr81u22zskfuI10eEz1X37tKePd++Dh+ryP3Gi7VjXxWtjcTqi6y03WixmZlnVbx+00obj3UhmehFdqz48vNPnMfIut7xvFkpR+Sbi0QePbT7Ri/ackbjg9G0ePu2cm6cumA2iidynlH/Evm31VjMjr2JbCfahy4d/7da18LrmulPo42n4f877jdane04VoeF31R0XL/jfiL75Gjl7Tg/cr+RZYo1nlgRra+M1TbM7iPa+Yx8HTk9XNbwtbCZfYSPTbS4Yo31seqGmX46vG6sehwvHjN9kdX260QfZabckeOGnSRlrFgiy27mfUi09hjvXFoZY4zGD6si+4p4dahj7B3ndVwvrF+/tP6VOk8o1DVK5/f7T9x611WFf+6w46ATFm7s4f87Tou3rcj/O9qz50Tl7bh85N/RXsfScXuRjSkUOjGgRMZ25Mi3ZYi1n2jLdXzTFK8sHUUO5h2PdVjk8Yx23DtuP9a5ipzmxE9ZRttuZJxHjpx6nGOVwwlm99HxeHe80IlVnlj7iGSnXMk6FuFth3XcR7S6Z6aedoxXit9OO4pcLrK9RO4v2vRo24+1/1ht2iiueMfBqIxmymGlL0vGPCPx6kC0OmpnX/H61cjpZvYb7bwZxRWt/kfbdrw+zqg+WimTUbzx9hWrLJHrxGpX8cpoJjazy3dsi07UIyustpdYxyTRdmdUP8y2MzN1L96+jdqKUV9odqywcrzM9o1G9dXM9qz0D1aun2JdM1s9jtHqRWQMsZjtK+KtHzk+G8Vjpz6Gt2Pn2sdsXbFzzWl0/KJto+P1fse/rcTRMYHS8fhHLh/rfYrRuY21nVjrxHqfE+4XwutFK9uePVLv3t/+feaZ336vRnjZyOP0zTfSd76TnOvgFIj1/p8ERmfpWAnDr/v1i92QIkW7QAv/H62RR1uu47SOcUVb14p4sXWMJVoDN5OMibZ9qxfDsdhN6Njdn1nROkg7FyiJsDOwmbmYiVcuoxjsxG2Wlc7e6FjYqYN2Exh2ymo3gWH1oj5ZyYFo6yczgWHn4tDqPpOdwDCzXzsJjHjbj/fGyagfsNP/mInX7LE3+8bUCqvr2OlnEm1XiSRhEqkrVrdjNxERbz0745LZemK1rVpZLtnXB/G25/S2nZgeL6maaGyJ1nGn+iez61pdx+xxNLpWj7WMmboTbRmja2Gzyex4412842cm8R9rebP7car/TDOx3v9npyCWzNSvX/TXZi+G4y0Xue14wo9h2Fk3FrODhN1MYLT13JhVtJLZN5LowJssid7h4NZySe6OrasK9zdd/ZMA6oazOJ7u1ZXbaaIyuexdVbSxJVPPY/jxJLN3DhixehyTedyNtm1lTLFzPWJ1zMrUOtiJTH0HxrZt21RZWSlJ2rt3r8rLy1VRUaH58+fr+PHjkqTVq1fr5ptv1i233KINGzZIklpaWlRVVaWKigrdeeedOnjwoCRp69atmjhxoiZNmqTf/OY3yShX19QZFd6JhEU0kYmRTJSf33U7LbPP8YU78a5aznRl5vxFPrvZGfr1o744yYnnbQEgXTC2fKtfv/jHg+u3E5JdfsbnTmGYwHj22Wc1b948BYNBSdIvfvEL3XfffXrxxRcVCoW0fv167d+/X3V1dVq1apX+5V/+RYsXL1Zra6tWrlypkpISvfjii7rpppu0dOlSSdL8+fNVW1urlStXatu2bdqxY0dySwlr7DS+ZCVG0DkY2Lo2M+evKyfYcALtFICTSIoCzur4HWdIGsMERnFxsZYsWdL+eseOHbr88sslSaNGjdL777+vhoYGDR06VLm5uSosLFRxcbEaGxtVX1+vkSNHti/r8/kUCATU2tqq4uJieTwelZWVyefzJal4LuNUZU723Q7hi2QAAOC8VNwRBUQiKYpky9R+jjaVVIYJjNGjRys7+9uvygiFQvL875tbr9erpqYmBQIBFRYWti/j9XoVCAROmt5x2YKCgpOWbWpqcqxAruZUZeZuB6Dr4o0LAO6IApAJ+FAUSWD5Szy7dfs259Hc3KwePXqooKBAzc3NJ00vLCw8aXq8ZXv06GG432AwKL/fbzVcV+jSv56SKi0tOnbsmLI7JLuisfLrNB2XjVwv3uuO9S5yWrR9R86Lti2zr60ys69oZTF7LGLty2w8sZaPd8yM5kc7P3bXMRNbrPLFW/ek9W28aTllP3G+hMrtv9gULb5Y9STasTdTXyPXsTIvLF5dtVMP480zs7yZ9hNtW07VhWOBgCTpr599dsp+jNjtB6Itb7asVvsUs+WIto5RXxsv1pPK07+/lJ+vY4HASWOfUX8Vrx7FqqtW/zYqg9E5MnPezJzDeOubPRbRmOmXjLYRb1t2GV2b2Gnv8eqxlWMdb5tm61/k+tHiireOmWmx4jVqx0bTjeZZicvqOGa2P7V7nZfIdZ9Vbr1msTtGuLEsUvRxqSsz9TOqn3/+uX76059q9erVmjFjhqZMmaIrrrhCjzzyiIYPH67LLrtMU6dO1Zo1a9Ta2qqJEyfqlVde0YoVK9Tc3KyqqiqtW7dOH3zwgRYsWKBx48ZpyZIl6tu3r6ZPn657771XQ4YMiRuDmyuFI4x+bs7KOpHzO+Pn3oz2Gfk68ieRzMZq5+fVrCzbmcfKynaT/TNpVvaR6E+qWVm+s89Hoj9XZqfNRVvH7E/m2f05Oys/b2anbVr9qTQ7rLQBJ+ZZjdfqPu3UPSd+gtDoXCerPzXah9ltWe0LzR57q/GZ4VT/GK9NJvvXXey2Jae3Y+a8261XTvZ1Rv1nomNOtHlOtAmz23e6H++s6XZjc3KcTcY+rcaUrH42chkrY4vda1+rbTuR9x92rmOd6gusLtvFOfYzqnPnztXDDz+sxYsXa8CAARo9erSysrJUWVmpiooKhUIh2mvNGgAAG89JREFUzZo1S3l5eSovL9fcuXNVXl6unJwc1dbWSpIWLFig2bNnq62tTWVlZYbJi4yWrreYpmu5AAAAAABJYeoODDfI2DswElnHzqfBicQTb59mP0lK9JM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      "text/plain": [
       "<Figure size 1080x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "price_volume(dollar_bars.set_index('timestamp'), \n",
    "             suptitle=f'Dollar Bars | {stock} | {pd.to_datetime(date).date()}', \n",
    "             fname='dollar_bars')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": true,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "230.909px"
   },
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}